近日，一篇关于语言模型对齐研究的论文被ICML 2024接收，并荣幸地入选为本次大会的Spotlight Presentation。该论文由瑞士、英国和法国的三所大学的博士生以及Google DeepMind和Google Research的研究人员合作完成。
随着人工智能技术的不断发展，语言模型已成为当今研究的热点之一。然而，当前的语言模型常常存在幻觉现象，其产生的内容有时难以符合人类的预期和偏好。针对这一问题，该论文提出了一种新的解码中重新对齐的方法，旨在让语言模型更少幻觉、更符合人类偏好。
据了解，该论文的通讯作者Tianlin Liu和Mathieu Blondel分别来自瑞士巴塞尔大学和Google DeepMind Paris。他们及其团队通过深入研究，提出了一系列创新的解决方案，为语言模型的发展开辟了新的方向。
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此外，该论文已在开放评审平台OpenReview上发布，并提供代码地址供公众查阅和参考。公众可以通过访问论文地址：https://openreview.net/forum?id=n8g6WMxt09¬eId=E3VVDPVOPZ 以及代码地址：https://github.com/liutianlin0121/decoding-time-realig 了解更多详情。
此次研究成果对于语言模型的发展具有里程碑意义，期待未来有更多的研究者和团队在该领域取得更多突破，推动人工智能技术的不断进步。
英语如下：
News Title: “New Breakthrough in Language Model Decoding: Alignment Research Selected for ICML 2024 Spotlight”
Keywords: language model alignment research, ICML-2024 Spotlight paper selection, cutting-edge technology exploration in AI field
News Content:
ICML 2024 focuses on language model alignment research, with a new paper selected as a Spotlight Presentation. Recently, a paper on language model alignment research was accepted by ICML 2024 and honored as a Spotlight Presentation. The paper was collaboratively completed by doctoral students from three universities in Switzerland, the UK, and France, as well as researchers from Google DeepMind and Google Research.
With the continuous development of artificial intelligence technology, language models have become one of the hotspots of current research. However, current language models often suffer from hallucination, producing content that is sometimes difficult to align with human expectations and preferences. In response to this issue, the paper proposes a new method of re-alignment during decoding, aimed at making language models less hallucinatory and more aligned with human preferences.
It is understood that the corresponding authors of the paper are Tianlin Liu and Mathieu Blondel from the University of Basel, Switzerland, and Google DeepMind Paris. They and their team have proposed a series of innovative solutions through deep research, opening up new directions for the development of language models.
The Machine Heart AIxiv column is one of the leading columns worldwide for publishing academic and technical content, and has been committed to promoting academic communication and dissemination for years. If you have excellent work to share, please feel free to submit or contact us for reporting. Please send your contributions to the designated email: liyazhou@jiqizhixin.com; zhaoyunfeng@jiqizhixin.com.
In addition, the paper has been published on the open review platform OpenReview, and the code address is available for public review and reference. The public can learn more by visiting the paper address: https://openreview.net/forum?id=n8g6WMxt09¬eId=E3VVDPVOPZ and the code address: https://github.com/liutianlin0121/decoding-time-realig.
This research achievement is of milestone significance for the development of language models. We look forward to more researchers and teams making breakthroughs in this field and continuously advancing the progress of artificial intelligence technology.
【来源】https://www.jiqizhixin.com/articles/2024-07-01-8
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